Overview

Dataset statistics

Number of variables17
Number of observations97275
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.6 MiB
Average record size in memory136.0 B

Variable types

Numeric16
Categorical1

Warnings

sema_diff is highly correlated with lema_diffHigh correlation
lema_diff is highly correlated with sema_diffHigh correlation
small_sema_slope is highly correlated with long_sema_slopeHigh correlation
long_sema_slope is highly correlated with small_sema_slopeHigh correlation
spread_avg has 94637 (97.3%) zeros Zeros
tick_sd has 37680 (38.7%) zeros Zeros
sema_diff has 46828 (48.1%) zeros Zeros
lema_diff has 50467 (51.9%) zeros Zeros
diff has 28962 (29.8%) zeros Zeros
avg_gain has 44661 (45.9%) zeros Zeros
avg_loss has 44646 (45.9%) zeros Zeros
ssma_diff has 51439 (52.9%) zeros Zeros
lsma_diff has 55268 (56.8%) zeros Zeros
sma_diff has 76974 (79.1%) zeros Zeros
max_gap has 38468 (39.5%) zeros Zeros
min_gap has 37555 (38.6%) zeros Zeros
ema_diff has 90921 (93.5%) zeros Zeros

Reproduction

Analysis started2021-02-06 07:11:27.004599
Analysis finished2021-02-06 07:12:05.154423
Duration38.15 seconds
Software versionpandas-profiling v2.10.0
Download configurationconfig.yaml

Variables

spread_avg
Real number (ℝ≥0)

ZEROS

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.674119764 × 106
Minimum0
Maximum0.0011
Zeros94637
Zeros (%)97.3%
Memory size760.1 KiB
2021-02-06T15:12:05.213606image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0.0011
Range0.0011
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.553916608 × 105
Coefficient of variation (CV)6.951097873
Kurtosis189.9811448
Mean3.674119764 × 106
Median Absolute Deviation (MAD)0
Skewness10.76549844
Sum0.3574
Variance6.522490038 × 1010
MonotocityNot monotonic
2021-02-06T15:12:05.291744image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
094637
97.3%
0.00012005
 
2.1%
0.0002428
 
0.4%
0.0003154
 
0.2%
0.000434
 
< 0.1%
0.00055
 
< 0.1%
0.00064
 
< 0.1%
0.00073
 
< 0.1%
0.00083
 
< 0.1%
0.0011
 
< 0.1%
ValueCountFrequency (%)
094637
97.3%
0.00012005
 
2.1%
0.0002428
 
0.4%
0.0003154
 
0.2%
0.000434
 
< 0.1%
ValueCountFrequency (%)
0.00111
 
< 0.1%
0.0011
 
< 0.1%
0.00083
< 0.1%
0.00073
< 0.1%
0.00064
< 0.1%

tick_sd
Real number (ℝ≥0)

ZEROS

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.583705988 × 105
Minimum0
Maximum0.0014
Zeros37680
Zeros (%)38.7%
Memory size760.1 KiB
2021-02-06T15:12:05.369851image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.0001
Q30.0001
95-th percentile0.0001
Maximum0.0014
Range0.0014
Interquartile range (IQR)0.0001

Descriptive statistics

Standard deviation5.970141431 × 105
Coefficient of variation (CV)0.9068055958
Kurtosis18.67945787
Mean6.583705988 × 105
Median Absolute Deviation (MAD)0
Skewness1.593747527
Sum6.4043
Variance3.564258871 × 109
MonotocityNot monotonic
2021-02-06T15:12:05.459224image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.000156103
57.7%
037680
38.7%
0.00022936
 
3.0%
0.0003375
 
0.4%
0.0004100
 
0.1%
0.000529
 
< 0.1%
0.000624
 
< 0.1%
0.000711
 
< 0.1%
0.0015
 
< 0.1%
0.00124
 
< 0.1%
Other values (4)8
 
< 0.1%
ValueCountFrequency (%)
037680
38.7%
0.000156103
57.7%
0.00022936
 
3.0%
0.0003375
 
0.4%
0.0004100
 
0.1%
ValueCountFrequency (%)
0.00141
 
< 0.1%
0.00124
< 0.1%
0.00112
 
< 0.1%
0.0015
< 0.1%
0.00093
< 0.1%

sema_diff
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct25
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.00462606 × 107
Minimum-0.0011
Maximum0.0015
Zeros46828
Zeros (%)48.1%
Memory size760.1 KiB
2021-02-06T15:12:05.537330image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-0.0011
5-th percentile-0.0001
Q1-0.0001
median0
Q30.0001
95-th percentile0.0001
Maximum0.0015
Range0.0026
Interquartile range (IQR)0.0002

Descriptive statistics

Standard deviation9.60454422 × 105
Coefficient of variation (CV)-479.1189943
Kurtosis5.928257963
Mean-2.00462606 × 107
Median Absolute Deviation (MAD)0.0001
Skewness0.05739741494
Sum-0.0195
Variance9.224726967 × 109
MonotocityNot monotonic
2021-02-06T15:12:05.631056image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
046828
48.1%
0.000121678
22.3%
-0.000120958
21.5%
-0.00023291
 
3.4%
0.00022992
 
3.1%
-0.0003571
 
0.6%
0.0003456
 
0.5%
-0.0004147
 
0.2%
0.0004143
 
0.1%
-0.000554
 
0.1%
Other values (15)157
 
0.2%
ValueCountFrequency (%)
-0.00111
 
< 0.1%
-0.0012
 
< 0.1%
-0.00084
 
< 0.1%
-0.000714
< 0.1%
-0.000630
< 0.1%
ValueCountFrequency (%)
0.00151
< 0.1%
0.00131
< 0.1%
0.00121
< 0.1%
0.00112
< 0.1%
0.0011
< 0.1%

lema_diff
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct22
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-5.345669494 × 108
Minimum-0.001
Maximum0.0013
Zeros50467
Zeros (%)51.9%
Memory size760.1 KiB
2021-02-06T15:12:05.728170image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-0.001
5-th percentile-0.0001
Q1-0
median-0
Q30
95-th percentile0.0001
Maximum0.0013
Range0.0023
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.894294186 × 105
Coefficient of variation (CV)-1663.831667
Kurtosis5.494937795
Mean-5.345669494 × 108
Median Absolute Deviation (MAD)0
Skewness0.0525030109
Sum-0.0052
Variance7.910846907 × 109
MonotocityNot monotonic
2021-02-06T15:12:05.821904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
050467
51.9%
0.000120626
21.2%
-0.000120013
 
20.6%
-0.00022615
 
2.7%
0.00022377
 
2.4%
-0.0003441
 
0.5%
0.0003373
 
0.4%
-0.0004110
 
0.1%
0.000494
 
0.1%
0.000545
 
< 0.1%
Other values (12)114
 
0.1%
ValueCountFrequency (%)
-0.0011
 
< 0.1%
-0.00092
 
< 0.1%
-0.00081
 
< 0.1%
-0.00078
< 0.1%
-0.000619
< 0.1%
ValueCountFrequency (%)
0.00131
 
< 0.1%
0.00112
 
< 0.1%
0.0013
 
< 0.1%
0.00084
< 0.1%
0.00079
< 0.1%

diff
Real number (ℝ)

ZEROS

Distinct46
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.220508867 × 107
Minimum-0.0024
Maximum0.0038
Zeros28962
Zeros (%)29.8%
Memory size760.1 KiB
2021-02-06T15:12:05.915630image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-0.0024
5-th percentile-0.0002
Q1-0.0001
median0
Q30.0001
95-th percentile0.0002
Maximum0.0038
Range0.0062
Interquartile range (IQR)0.0002

Descriptive statistics

Standard deviation0.0001649373894
Coefficient of variation (CV)-742.7909514
Kurtosis11.28646993
Mean-2.220508867 × 107
Median Absolute Deviation (MAD)0.0001
Skewness0.1276926376
Sum-0.0216
Variance2.720434241 × 108
MonotocityNot monotonic
2021-02-06T15:12:06.009354image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
-028962
29.8%
0.000120765
21.3%
-0.000119997
20.6%
-0.00029072
 
9.3%
0.00028968
 
9.2%
0.00033146
 
3.2%
-0.00033055
 
3.1%
-0.00041068
 
1.1%
0.0004931
 
1.0%
-0.0005373
 
0.4%
Other values (36)938
 
1.0%
ValueCountFrequency (%)
-0.00241
< 0.1%
-0.00221
< 0.1%
-0.00211
< 0.1%
-0.0021
< 0.1%
-0.00192
< 0.1%
ValueCountFrequency (%)
0.00381
< 0.1%
0.00251
< 0.1%
0.00242
< 0.1%
0.00221
< 0.1%
0.00211
< 0.1%

avg_gain
Real number (ℝ≥0)

ZEROS

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.628578772 × 105
Minimum0
Maximum0.0005
Zeros44661
Zeros (%)45.9%
Memory size760.1 KiB
2021-02-06T15:12:06.103081image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.0001
Q30.0001
95-th percentile0.0001
Maximum0.0005
Range0.0005
Interquartile range (IQR)0.0001

Descriptive statistics

Standard deviation5.464090768 × 105
Coefficient of variation (CV)0.9707762811
Kurtosis0.4772623481
Mean5.628578772 × 105
Median Absolute Deviation (MAD)0
Skewness0.4174148373
Sum5.4752
Variance2.985628792 × 109
MonotocityNot monotonic
2021-02-06T15:12:06.182495image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0.000150826
52.2%
044661
45.9%
0.00021497
 
1.5%
0.0003239
 
0.2%
0.000445
 
< 0.1%
0.00057
 
< 0.1%
ValueCountFrequency (%)
044661
45.9%
0.000150826
52.2%
0.00021497
 
1.5%
0.0003239
 
0.2%
0.000445
 
< 0.1%
ValueCountFrequency (%)
0.00057
 
< 0.1%
0.000445
 
< 0.1%
0.0003239
 
0.2%
0.00021497
 
1.5%
0.000150826
52.2%

avg_loss
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.652428682 × 105
Minimum0
Maximum0.0007
Zeros44646
Zeros (%)45.9%
Memory size760.1 KiB
2021-02-06T15:12:06.260597image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.0001
Q30.0001
95-th percentile0.0001
Maximum0.0007
Range0.0007
Interquartile range (IQR)0.0001

Descriptive statistics

Standard deviation5.496195102 × 105
Coefficient of variation (CV)0.9723599202
Kurtosis0.8847705382
Mean5.652428682 × 105
Median Absolute Deviation (MAD)0
Skewness0.4444679813
Sum5.4984
Variance3.02081606 × 109
MonotocityNot monotonic
2021-02-06T15:12:06.338704image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.000150562
52.0%
044646
45.9%
0.00021845
 
1.9%
0.0003177
 
0.2%
0.000432
 
< 0.1%
0.00057
 
< 0.1%
0.00064
 
< 0.1%
0.00072
 
< 0.1%
ValueCountFrequency (%)
044646
45.9%
0.000150562
52.0%
0.00021845
 
1.9%
0.0003177
 
0.2%
0.000432
 
< 0.1%
ValueCountFrequency (%)
0.00072
 
< 0.1%
0.00064
 
< 0.1%
0.00057
 
< 0.1%
0.000432
 
< 0.1%
0.0003177
0.2%

rsi
Real number (ℝ≥0)

Distinct90531
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.09417742
Minimum0
Maximum99.9999
Zeros6
Zeros (%)< 0.1%
Memory size760.1 KiB
2021-02-06T15:12:06.463675image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20.44418
Q136.80385
median49.9514
Q363.203
95-th percentile80.31747
Maximum99.9999
Range99.9999
Interquartile range (IQR)26.39915

Descriptive statistics

Standard deviation18.23571151
Coefficient of variation (CV)0.3640285647
Kurtosis-0.5069269952
Mean50.09417742
Median Absolute Deviation (MAD)13.1937
Skewness0.02980853398
Sum4872911.108
Variance332.5411741
MonotocityNot monotonic
2021-02-06T15:12:06.573024image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.999919
 
< 0.1%
06
 
< 0.1%
64.82224
 
< 0.1%
55.10984
 
< 0.1%
34.81154
 
< 0.1%
51.97194
 
< 0.1%
49.09834
 
< 0.1%
55.70814
 
< 0.1%
45.79214
 
< 0.1%
54.26794
 
< 0.1%
Other values (90521)97218
99.9%
ValueCountFrequency (%)
06
< 0.1%
0.13111
 
< 0.1%
0.1341
 
< 0.1%
0.35231
 
< 0.1%
0.36661
 
< 0.1%
ValueCountFrequency (%)
99.999919
< 0.1%
99.97251
 
< 0.1%
99.80591
 
< 0.1%
99.80291
 
< 0.1%
99.79421
 
< 0.1%

ssma_diff
Real number (ℝ)

ZEROS

Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.467232074 × 107
Minimum-0.0011
Maximum0.0009
Zeros51439
Zeros (%)52.9%
Memory size760.1 KiB
2021-02-06T15:12:06.666752image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-0.0011
5-th percentile-0.0001
Q10
median-0
Q30
95-th percentile0.0001
Maximum0.0009
Range0.002
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.645992108 × 105
Coefficient of variation (CV)-350.4328676
Kurtosis4.430447189
Mean-2.467232074 × 107
Median Absolute Deviation (MAD)0
Skewness0.01963178616
Sum-0.024
Variance7.475317954 × 109
MonotocityNot monotonic
2021-02-06T15:12:06.760485image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
051439
52.9%
0.000120194
 
20.8%
-0.000119901
 
20.5%
-0.00022454
 
2.5%
0.00022254
 
2.3%
-0.0003383
 
0.4%
0.0003345
 
0.4%
-0.0004109
 
0.1%
0.000474
 
0.1%
0.000534
 
< 0.1%
Other values (10)88
 
0.1%
ValueCountFrequency (%)
-0.00111
 
< 0.1%
-0.00091
 
< 0.1%
-0.00083
 
< 0.1%
-0.00073
 
< 0.1%
-0.000610
< 0.1%
ValueCountFrequency (%)
0.00091
 
< 0.1%
0.00088
 
< 0.1%
0.000711
 
< 0.1%
0.000616
< 0.1%
0.000534
< 0.1%

lsma_diff
Real number (ℝ)

ZEROS

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.806476484 × 107
Minimum-0.0011
Maximum0.0008
Zeros55268
Zeros (%)56.8%
Memory size760.1 KiB
2021-02-06T15:12:06.854203image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-0.0011
5-th percentile-0.0001
Q10
median0
Q30
95-th percentile0.0001
Maximum0.0008
Range0.0019
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.989898031 × 105
Coefficient of variation (CV)-284.694993
Kurtosis4.391854056
Mean-2.806476484 × 107
Median Absolute Deviation (MAD)0
Skewness0.009993661051
Sum-0.0273
Variance6.383847054 × 109
MonotocityNot monotonic
2021-02-06T15:12:06.932310image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
055268
56.8%
0.000118846
 
19.4%
-0.000118817
 
19.3%
-0.00021825
 
1.9%
0.00021726
 
1.8%
-0.0003313
 
0.3%
0.0003263
 
0.3%
-0.000476
 
0.1%
0.000456
 
0.1%
0.000526
 
< 0.1%
Other values (8)59
 
0.1%
ValueCountFrequency (%)
-0.00111
 
< 0.1%
-0.00081
 
< 0.1%
-0.00076
 
< 0.1%
-0.00067
< 0.1%
-0.000516
< 0.1%
ValueCountFrequency (%)
0.00082
 
< 0.1%
0.00077
 
< 0.1%
0.000619
 
< 0.1%
0.000526
< 0.1%
0.000456
0.1%

sma_diff
Real number (ℝ)

ZEROS

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.734515549 × 107
Minimum-0.0007
Maximum0.0006
Zeros76974
Zeros (%)79.1%
Memory size760.1 KiB
2021-02-06T15:12:07.026043image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-0.0007
5-th percentile-0.0001
Q1-0
median-0
Q30
95-th percentile0.0001
Maximum0.0006
Range0.0013
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.914223281 × 105
Coefficient of variation (CV)-179.7109284
Kurtosis6.050875374
Mean-2.734515549 × 107
Median Absolute Deviation (MAD)0
Skewness0.003526862233
Sum-0.0266
Variance2.414959045 × 109
MonotocityNot monotonic
2021-02-06T15:12:07.104157image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
076974
79.1%
-0.00019844
 
10.1%
0.00019707
 
10.0%
-0.0002353
 
0.4%
0.0002278
 
0.3%
-0.000347
 
< 0.1%
0.000342
 
< 0.1%
0.000412
 
< 0.1%
-0.00048
 
< 0.1%
0.00055
 
< 0.1%
Other values (3)5
 
< 0.1%
ValueCountFrequency (%)
-0.00071
 
< 0.1%
-0.00052
 
< 0.1%
-0.00048
 
< 0.1%
-0.000347
 
< 0.1%
-0.0002353
0.4%
ValueCountFrequency (%)
0.00062
 
< 0.1%
0.00055
 
< 0.1%
0.000412
 
< 0.1%
0.000342
 
< 0.1%
0.0002278
0.3%

max_gap
Real number (ℝ≥0)

ZEROS

Distinct36
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0001750717039
Minimum0
Maximum0.0049
Zeros38468
Zeros (%)39.5%
Memory size760.1 KiB
2021-02-06T15:12:07.199189image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.0001
Q30.0003
95-th percentile0.0006
Maximum0.0049
Range0.0049
Interquartile range (IQR)0.0003

Descriptive statistics

Standard deviation0.0002291780514
Coefficient of variation (CV)1.309052498
Kurtosis17.51463623
Mean0.0001750717039
Median Absolute Deviation (MAD)0.0001
Skewness2.742295057
Sum17.0301
Variance5.252257926 × 108
MonotocityNot monotonic
2021-02-06T15:12:07.308539image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
038468
39.5%
0.000118180
18.7%
0.000214338
 
14.7%
0.00039798
 
10.1%
0.00046413
 
6.6%
0.00053970
 
4.1%
0.00062331
 
2.4%
0.00071448
 
1.5%
0.0008801
 
0.8%
0.0009480
 
0.5%
Other values (26)1048
 
1.1%
ValueCountFrequency (%)
038468
39.5%
0.000118180
18.7%
0.000214338
 
14.7%
0.00039798
 
10.1%
0.00046413
 
6.6%
ValueCountFrequency (%)
0.00492
< 0.1%
0.00411
< 0.1%
0.00381
< 0.1%
0.00371
< 0.1%
0.00351
< 0.1%

min_gap
Real number (ℝ)

ZEROS

Distinct39
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.0001751087124
Minimum-0.0042
Maximum0
Zeros37555
Zeros (%)38.6%
Memory size760.1 KiB
2021-02-06T15:12:07.402269image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-0.0042
5-th percentile-0.0006
Q1-0.0003
median-0.0001
Q30
95-th percentile0
Maximum0
Range0.0042
Interquartile range (IQR)0.0003

Descriptive statistics

Standard deviation0.0002248351011
Coefficient of variation (CV)-1.283974384
Kurtosis20.92643951
Mean-0.0001751087124
Median Absolute Deviation (MAD)0.0001
Skewness-2.896363137
Sum-17.0337
Variance5.055082268 × 108
MonotocityNot monotonic
2021-02-06T15:12:07.511616image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
037555
38.6%
-0.000118359
18.9%
-0.000214640
 
15.1%
-0.000310321
 
10.6%
-0.00046732
 
6.9%
-0.00054044
 
4.2%
-0.00062206
 
2.3%
-0.00071275
 
1.3%
-0.0008775
 
0.8%
-0.0009461
 
0.5%
Other values (29)907
 
0.9%
ValueCountFrequency (%)
-0.00423
< 0.1%
-0.00412
< 0.1%
-0.00372
< 0.1%
-0.00362
< 0.1%
-0.00353
< 0.1%
ValueCountFrequency (%)
037555
38.6%
-0.000118359
18.9%
-0.000214640
 
15.1%
-0.000310321
 
10.6%
-0.00046732
 
6.9%

small_sema_slope
Real number (ℝ)

HIGH CORRELATION

Distinct90577
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3816632814
Minimum-89.3214
Maximum89.3537
Zeros0
Zeros (%)0.0%
Memory size760.1 KiB
2021-02-06T15:12:07.636587image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-89.3214
5-th percentile-85.16269
Q1-77.05445
median2.9331
Q377.07555
95-th percentile84.98769
Maximum89.3537
Range178.6751
Interquartile range (IQR)154.13

Descriptive statistics

Standard deviation72.03570253
Coefficient of variation (CV)188.741506
Kurtosis-1.833594382
Mean0.3816632814
Median Absolute Deviation (MAD)76.6232
Skewness-0.0123551797
Sum37126.2957
Variance5189.142439
MonotocityNot monotonic
2021-02-06T15:12:07.745936image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
82.96795
 
< 0.1%
80.70015
 
< 0.1%
-82.87554
 
< 0.1%
85.98654
 
< 0.1%
-84.37374
 
< 0.1%
-84.10864
 
< 0.1%
-83.3194
 
< 0.1%
82.46574
 
< 0.1%
83.84634
 
< 0.1%
-84.09584
 
< 0.1%
Other values (90567)97233
> 99.9%
ValueCountFrequency (%)
-89.32141
< 0.1%
-89.29711
< 0.1%
-89.22181
< 0.1%
-89.09791
< 0.1%
-89.09241
< 0.1%
ValueCountFrequency (%)
89.35371
< 0.1%
89.35361
< 0.1%
89.28051
< 0.1%
89.27541
< 0.1%
89.24681
< 0.1%

long_sema_slope
Real number (ℝ)

HIGH CORRELATION

Distinct90758
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2796654649
Minimum-89.2818
Maximum89.266
Zeros0
Zeros (%)0.0%
Memory size760.1 KiB
2021-02-06T15:12:07.870908image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-89.2818
5-th percentile-84.9107
Q1-76.41475
median1.7959
Q376.45635
95-th percentile84.74138
Maximum89.266
Range178.5478
Interquartile range (IQR)152.8711

Descriptive statistics

Standard deviation71.42078063
Coefficient of variation (CV)255.3793356
Kurtosis-1.825647137
Mean0.2796654649
Median Absolute Deviation (MAD)76.2495
Skewness-0.009140784326
Sum27204.4581
Variance5100.927906
MonotocityNot monotonic
2021-02-06T15:12:07.984351image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84.06125
 
< 0.1%
84.77385
 
< 0.1%
82.56315
 
< 0.1%
-77.85095
 
< 0.1%
-84.3355
 
< 0.1%
81.35935
 
< 0.1%
82.56014
 
< 0.1%
83.25594
 
< 0.1%
83.54994
 
< 0.1%
-83.89874
 
< 0.1%
Other values (90748)97229
> 99.9%
ValueCountFrequency (%)
-89.28181
< 0.1%
-89.27051
< 0.1%
-89.16211
< 0.1%
-89.12971
< 0.1%
-89.09381
< 0.1%
ValueCountFrequency (%)
89.2661
< 0.1%
89.25621
< 0.1%
89.2481
< 0.1%
89.24761
< 0.1%
89.20521
< 0.1%

ema_diff
Real number (ℝ)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.909277821 × 107
Minimum-0.0004
Maximum0.0003
Zeros90921
Zeros (%)93.5%
Memory size760.1 KiB
2021-02-06T15:12:08.062459image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-0.0004
5-th percentile0
Q10
median-0
Q3-0
95-th percentile-0
Maximum0.0003
Range0.0007
Interquartile range (IQR)-0

Descriptive statistics

Standard deviation2.655253237 × 105
Coefficient of variation (CV)-91.26846595
Kurtosis16.89019235
Mean-2.909277821 × 107
Median Absolute Deviation (MAD)0
Skewness-0.08299948553
Sum-0.0283
Variance7.050369754 × 1010
MonotocityNot monotonic
2021-02-06T15:12:08.140564image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
090921
93.5%
-0.00013253
 
3.3%
0.00012960
 
3.0%
-0.000264
 
0.1%
0.000262
 
0.1%
0.000310
 
< 0.1%
-0.00034
 
< 0.1%
-0.00041
 
< 0.1%
ValueCountFrequency (%)
-0.00041
 
< 0.1%
-0.00034
 
< 0.1%
-0.000264
 
0.1%
-0.00013253
 
3.3%
090921
93.5%
ValueCountFrequency (%)
0.000310
 
< 0.1%
0.000262
 
0.1%
0.00012960
 
3.0%
090921
93.5%
-0.00013253
 
3.3%

direction
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size760.1 KiB
same
76530 
decrease
10637 
increase
10108 

Length

Max length8
Median length4
Mean length4.85304549
Min length4

Characters and Unicode

Total characters472080
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowsame
2nd rowsame
3rd rowsame
4th rowsame
5th rowdecrease
ValueCountFrequency (%)
same76530
78.7%
decrease10637
 
10.9%
increase10108
 
10.4%
2021-02-06T15:12:08.329321image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-02-06T15:12:08.391795image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
same76530
78.7%
decrease10637
 
10.9%
increase10108
 
10.4%

Most occurring characters

ValueCountFrequency (%)
e128657
27.3%
s97275
20.6%
a97275
20.6%
m76530
16.2%
c20745
 
4.4%
r20745
 
4.4%
d10637
 
2.3%
i10108
 
2.1%
n10108
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter472080
100.0%

Most frequent character per category

ValueCountFrequency (%)
e128657
27.3%
s97275
20.6%
a97275
20.6%
m76530
16.2%
c20745
 
4.4%
r20745
 
4.4%
d10637
 
2.3%
i10108
 
2.1%
n10108
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Latin472080
100.0%

Most frequent character per script

ValueCountFrequency (%)
e128657
27.3%
s97275
20.6%
a97275
20.6%
m76530
16.2%
c20745
 
4.4%
r20745
 
4.4%
d10637
 
2.3%
i10108
 
2.1%
n10108
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII472080
100.0%

Most frequent character per block

ValueCountFrequency (%)
e128657
27.3%
s97275
20.6%
a97275
20.6%
m76530
16.2%
c20745
 
4.4%
r20745
 
4.4%
d10637
 
2.3%
i10108
 
2.1%
n10108
 
2.1%

Interactions

2021-02-06T15:11:34.898640image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:35.101758image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:35.217378image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:35.326729image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:35.455211image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:35.556745image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:35.681716image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:35.806686image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:35.917377image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:36.045331image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:36.171814image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:36.287622image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:36.396969image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:36.523292image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:36.632637image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:36.741992image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:36.866964image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:37.000296image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:37.141415image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:37.280003image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:37.389354image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:37.529946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:37.654917image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:37.795508image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:37.925836image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:38.066427image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:38.176962image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:38.317555image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:38.442525image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:38.567497image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:38.692467image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:38.895544image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:39.020514image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:39.129864image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:39.256034image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:39.365379image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:39.490350image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:39.615320image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:39.740292image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:39.865262image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:39.974613image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:40.099583image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:40.218180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:40.327531image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:40.455171image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:40.564522image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:40.673869image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:40.798841image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:40.908190image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:41.017544image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:41.126890image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:41.253599image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:41.362944image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:41.487916image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:41.612886image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:41.722235image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:41.831584image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:41.940936image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:42.050285image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:42.160877image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:42.285879image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:42.395231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:42.535818image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:42.645175image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:42.770144image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:42.879492image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:43.004462image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:43.113811image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:43.240109image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:43.458809image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:43.568151image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:43.693129image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:43.818100image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:43.927451image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:44.052420image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:44.162956image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:44.272337image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:44.397309image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:44.522278image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:44.631622image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:44.740978image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:44.865950image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:44.975300image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:45.100270image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:45.217859image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:45.342832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:45.458373image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:45.567726image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:45.677068image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:45.786423image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:45.911395image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:46.029113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:46.155335image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:46.280340image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:46.405311image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:46.530282image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:46.655252image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:46.764603image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:46.889573image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:47.033184image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:47.155745image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:47.280753image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:47.405723image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:47.530693image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:47.655666image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:47.765013image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:47.888594image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:47.997978image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:48.107323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:48.217886image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:48.327244image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:48.436593image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:48.561564image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:48.686533image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:48.795883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:49.014585image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:49.123931image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:49.234602image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:49.359573image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:49.468923image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:49.578273image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:49.703243image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:49.828215image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:49.953186image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:50.078158image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:50.205957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:50.330932image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:50.458139image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:50.583104image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:50.708082image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:50.833051image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:50.958023image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:51.082994image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:51.209271image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:51.334245image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:51.459211image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:51.584183image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:51.709148image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:51.834124image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:51.959095image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:52.068444image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:52.194731image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:52.340825image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:52.454133image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:52.594724image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:52.720888image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:52.830238image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:52.955209image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:53.080179image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:53.206393image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:53.331370image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:53.440712image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:53.565683image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:53.690654image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:53.800003image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:53.924979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:54.034322image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:54.160586image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:54.285587image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:54.410569image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:54.535530image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:54.660498image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:54.769853image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:54.894824image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:55.004172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:55.129144image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:55.233241image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:55.358203image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:55.473832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:55.598804image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:55.833118image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:55.958094image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:56.083062image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:56.193727image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:56.318697image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:56.443668image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:56.568639image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:56.677987image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:56.787335image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:56.912275image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:57.021625image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:57.146595image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:57.257195image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:57.382164image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:57.491512image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:57.600862image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:57.710212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:57.819561image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:57.934328image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:58.059292image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:58.169943image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:58.279328image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:58.404294image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:58.513642image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:58.622997image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:58.732344image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:58.841692image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:58.966669image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:59.091636image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:59.202308image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:59.311657image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:59.436596image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:59.561598image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:59.670948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:59.795918image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:11:59.920892image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:00.045862image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:00.157997image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:00.267383image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:00.392349image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:00.506856image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:00.646720image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:00.789167image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:00.905623image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:01.014976image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:01.139948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:01.250643image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:01.375614image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:01.484964image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:01.609934image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:01.734905image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:01.844254image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:01.969226image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:02.078572image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:02.189203image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:02.314175image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:02.423523image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:02.548495image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:02.673467image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:02.810275image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:02.930135image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:03.053602image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:03.171998image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:03.296964image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:03.421934image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:03.546904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:03.671875image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:03.796847image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:03.921817image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-02-06T15:12:04.204283image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2021-02-06T15:12:08.469905image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-02-06T15:12:08.641740image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-02-06T15:12:08.829165image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-02-06T15:12:09.001001image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2021-02-06T15:12:04.469051image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
A simple visualization of nullity by column.
2021-02-06T15:12:04.812722image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

spread_avgtick_sdsema_difflema_diffdiffavg_gainavg_lossrsissma_difflsma_diffsma_diffmax_gapmin_gapsmall_sema_slopelong_sema_slopeema_diffdirection
00.00010.00000.00000.0000-0.00000.00000.000060.79420.00000.00000.00000.0000-0.000170.612873.94420.0000same
10.00010.00000.00000.00000.00000.00010.000062.40310.00000.00000.00000.0000-0.000166.988869.38400.0000same
20.00010.00000.00000.0000-0.00000.00010.000066.41630.00000.00000.00000.0000-0.000161.432664.51010.0000same
30.00010.0000-0.0000-0.0000-0.00010.00010.000062.3975-0.00000.00000.00000.00010.000034.360248.1935-0.0000same
40.00000.0001-0.0001-0.0000-0.00010.00010.000057.6051-0.0000-0.0000-0.00000.00020.0000-51.5325-27.3533-0.0000decrease
50.00000.0001-0.0001-0.0001-0.00030.00000.000144.7157-0.0001-0.0001-0.00000.00050.0000-79.4475-74.5238-0.0000decrease
60.00000.0000-0.0001-0.0001-0.00010.00000.000051.7796-0.0001-0.0001-0.00000.00050.0000-83.8210-82.0735-0.0000decrease
70.00000.0001-0.0002-0.0002-0.00030.00000.000132.2821-0.0002-0.0001-0.00010.00070.0000-85.6097-84.8072-0.0001same
80.00000.0002-0.0000-0.00000.00020.00000.000134.3185-0.0001-0.0001-0.00010.0004-0.0002-85.5224-85.2469-0.0000same
90.00000.0001-0.0000-0.0000-0.00010.00000.000129.8226-0.0001-0.0001-0.00010.0002-0.0002-84.0414-84.7329-0.0000same

Last rows

spread_avgtick_sdsema_difflema_diffdiffavg_gainavg_lossrsissma_difflsma_diffsma_diffmax_gapmin_gapsmall_sema_slopelong_sema_slopeema_diffdirection
972650.00000.0000-0.0001-0.0001-0.00010.00.000121.3367-0.0001-0.0001-0.00.00040.0000-83.7900-83.8918-0.0same
972660.00000.0000-0.0001-0.0001-0.00000.00.000121.4106-0.0001-0.0001-0.00.00030.0000-83.4840-83.6670-0.0same
972670.00000.0001-0.0001-0.0001-0.00010.00.000119.3442-0.0001-0.0001-0.00.00040.0000-83.6508-83.5229-0.0same
972680.00000.0001-0.0000-0.00000.00010.00.000111.0753-0.0001-0.0001-0.00.0002-0.0001-82.6085-82.9553-0.0same
972690.00000.0000-0.0001-0.0001-0.00010.00.000110.7551-0.0001-0.0001-0.00.00020.0000-80.9346-81.9282-0.0same
972700.00000.00010.0000-0.00000.00010.00.000118.5846-0.0000-0.0000-0.00.0001-0.0001-76.6986-78.8993-0.0same
972710.00000.0001-0.0000-0.0000-0.00010.00.000118.1345-0.0000-0.0000-0.00.00010.0000-70.7884-75.4659-0.0same
972720.00000.0000-0.0001-0.0001-0.00010.00.000117.7358-0.0000-0.0000-0.00.00020.0000-73.6280-73.3139-0.0same
972730.00000.0001-0.0001-0.0001-0.00010.00.000112.9851-0.0001-0.0000-0.00.00030.0000-77.0600-76.3334-0.0decrease
972740.00010.0001-0.0001-0.0001-0.00020.00.000113.0219-0.0001-0.0001-0.00.00050.0000-81.8753-79.9184-0.0same